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Automatically Linking Lexical Resources with Word Sense Embedding Models

Conference paper
Authors Luis Nieto Piña
Richard Johansson
Published in The Third Workshop on Semantic Deep Learning (SemDeep-3), August 20th, 2018, Santa Fe, New Mexico, USA / Luis Espinosa Anke, Thierry Declerck, Dagmar Gromann (eds.)
ISBN 978-1-948087-56-8
Publication year 2018
Published at Department of Swedish
Department of Computer Science and Engineering (GU)
Language en
Links www.dfki.de/web/forschung/iwi/publi...
Keywords word embeddings, Swedish language, neural network, semantics, deep learning
Subject categories Language Technology (Computational Linguistics)

Abstract

Automatically learnt word sense embeddings are developed as an attempt to refine the capabilities of coarse word embeddings. The word sense representations obtained this way are, however, sensitive to underlying corpora and parameterizations, and they might be difficult to relate to word senses as formally defined by linguists. We propose to tackle this problem by devising a mechanism to establish links between word sense embeddings and lexical resources created by experts. We evaluate the applicability of these links in a task to retrieve instances of Swedish word senses not present in the lexicon.

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